Using imprecise user knowledge to reduce redundancy in Association Rules

DOI

10.2991/ifsa-eusflat-15.2015.155How to use a DOI?

Keywords

Association Rules, Imprecise Knowledge, Knowledge Based Redundancy

Abstract

Redundancy is a handicap in association rules. It becomes a limitation to use rules models in order to support the decision-making process. A technique based on user knowledge has been proposed recently, which aims at eliminating redundancy. However, it ignores the imprecise nature of knowledge. In this paper, the notion of knowledge redundancy is generalized and a method to propagate the user certainty over derivate rules is developed. Certainty factor models are used. Obtained results have shown a model reduction of 50% with previous knowledge below 3%. This method improves the efficiency of association rules and the use of discovered association rules.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Julio Diaz
AU  - Carlos Molina
AU  - M. Amparo Vila
PY  - 2015/06
DA  - 2015/06
TI  - Using imprecise user knowledge to reduce redundancy in Association Rules
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1098
EP  - 1105
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.155
DO  - 10.2991/ifsa-eusflat-15.2015.155
ID  - Diaz2015/06
ER  -